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A novel reliability metric and optimization framework could save cloud services millions while enhancing user experience.
Structured evidence from upstream sources boosts LLM repair accuracy by up to 23 percentage points, revolutionizing how we adapt to breaking changes in software dependencies.
AgentTether repairs over 65% of failures in complex LLM tasks without modifying the agent, revolutionizing how we ensure reliability in AI deployments.
Autonomous web agents get a serious upgrade with WebXSkill, which lets them learn and execute skills with both code-level precision and human-readable guidance.
Stop wasting time on manual LLM domain adaptation: AutoAdapt automates the process and boosts accuracy by 25% over existing AutoML methods.
Forget hand-crafted benchmarks: this paper shows how LLMs can continuously generate relevant evaluation datasets for enterprise AI agents from just a few semi-structured documents.
